Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It usefully discloses the return type (a 0–1 score) despite there being no output schema, and explicitly warns the result is heuristic (僅供參考). However, it omits whether higher means more-AI or less-AI, any minimum input length, language assumptions, or reliability/determinism details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two compact clauses with the namespace tag, the action, the detected features, and the output range front-loaded. Efficient with no padding, though the bracketed site tag is of marginal value to an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-param tool with no annotations and no output schema, the description reasonably covers what it does and what it returns. The critical gap is the direction/interpretation of the 0–1 score and any input constraints, which an agent needs to use the result correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the single 'text' parameter is undocumented. The description's 檢查一段文字 loosely maps to it, which is enough for a trivially obvious one-parameter tool, but it adds no detail on format, length limits, or accepted languages.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (檢查/check) and resource (一段文字的 AI 生成特徵) and enumerates the exact detection signals: 常用語、排版、個人經驗用語、句長一致性. This lets an agent understand the tool's function precisely. It does not, however, position itself against the sibling voices__ tools (which retrieve human opinions/posts), so the differentiation is implicit rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no conditions for selecting this over alternatives, and no mention of when the tool is inappropriate. The only qualifier, 僅供參考 (for reference only), is a caveat about trusting the output, not usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.